Despite the rapid growth of the use of technology in many industries, agriculture continues to utilize manual labor to perform the tedious and often costly processes for growing vegetables, fruits, and other crops. One primary driver of the continued use of manual labor in agriculture is the need for guidance and consultation by experienced agronomists with respect to developing plants. Such guidance and consultation is crucial to the success of larger farms.
Agronomy is the science of producing and using plants for food, fuel, fiber, and land reclamation. Agronomy involves use of principles from a variety of arts including, for example, biology, chemistry, economics, ecology, earth science, and genetics. Modern agronomists are involved in issues such as improving quantity and quality of food production, managing the environmental impacts of agriculture, extracting energy from plants, and so on. Agronomists often specialize in areas such as crop rotation, irrigation and drainage, plant breeding, plant physiology, soil classification, soil fertility, weed control, and pest control.
The plethora of duties assumed by agronomists require critical thinking to solve problems. For example, when planning to improve crop yields, an agronomist must study a farm's crop production in order to discern the best ways to plant, harvest, and cultivate the plants, regardless of climate. Additionally, agronomists may identify and address anomalies from normal growth patterns to ensure proper development. To these ends, the agronomist must continually monitor progress to ensure optimal results. For example, an agronomist may look for indicators developmental anomalies of such as disease (e.g., rings or fungi indicative of blight), pest infestation (e.g., abnormal holes in plants indicative that insects or rodents are eating portions of the plants), poor growth (e.g., smaller size of plants or numbers of fruit), and the like.
Reliance on manual observation of plants is time-consuming, expensive, and subject to human error. As a result, some existing solutions for automatic plant monitoring have been developed. Some existing solutions utilize machine vision to analyze multimedia, and may capture the multimedia via drones and other vehicles equipped with capturing devices. Such existing solutions typically obtain images from a wide upper angle of the examined environment (e.g., fields, orchards, etc.), in which the monitored plants are growing.
Existing solutions for plant monitoring face challenges in efficiently and accurately identifying anomalies and, consequently, cases in which external intervention may be required. More specifically, especially when implemented in larger farm areas, such solutions face significant challenges, even prior to determining appropriate responses to developmental issues, in identifying early signs and symptoms of anomalies.
It would therefore be advantageous to provide a solution that would overcome the challenges noted above.